title: Leveraging Markov models to compute prevalence estimates for a regional breast cancer registry.
abstract: Hospital cancer registries can be a reliable source for comparative effectiveness research. We used an expanded Markov model to estimate breast cancer prevalence for a distinct region in Germany. Thereby, transition probabilities were computed with patient information gained directly from the dataset. A first validation was executed by comparing the results with numbers obtained by another prevalence estimation technique.
authors.affiliation: Dept. of Medical Informatics, Heilbronn University, Germany.
authors.forename: Monika
authors.initials: M
authors.lastname: Pobiruchin
authors.forename: Meinhard
authors.initials: M
authors.lastname: Kieser
authors.forename: Wendelin
authors.initials: W
authors.lastname: Schramm
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001943:Breast Neoplasms / Q000453:epidemiology*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D005260:Female; D005858:Germany / Q000453:epidemiology; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D008390:Markov Chains; D008875:Middle Aged; D015233:Models, Statistical; D015995:Prevalence; D016016:Proportional Hazards Models; D012042:Registries; D012307:Risk Factors